Inspired by complex systems in nature, we will present some unique features of mammalian sensory systems from a Neuroscience perspective. Many of these algorithmic and architectural features are not in current generation Deep Learning systems. Drawing from our recent work on Neural Networks and Capsule Networks with Generative and Attentional mechanisms, we show how these features can be incorporated into next generation Deep Learning systems. Real-time sensory processing, scene analysis, and object recognition are needed before vision systems can become practical in Autonomous Vehicles. Multi-modal integration is natural in the next generation Deep Learning systems and we discuss how auditory signals can help with vision in these systems. We end the talk with a discussion on how such systems, with “Neuroscience Inside”, can make Autonomous Vehicles see like humans. KP Unnikrishnan eNeuroLearn, Ann Arbor, MI Co-sponsored by: Subramaniam Ganesan Speaker(s): Dr KP Unnikrishnan, Agenda: 6:00 PM – Welcome and Introductions, Chapter business update; 6:05 PM – Start of talk 7:00 PM – Formal end of Talk; Start of Q & A; Group Discussion 7:30 PM – Wrap Up Room: Digital, Bldg: Virtual, Rochester, Michigan, United States, 48309-4479, Virtual: https://events.vtools.ieee.org/m/310139